2017-040: Optimal operation of an energy management system for a grid-connected smart building considering PV uncertainty and stochastic EVs’ driving schedule

D. Thomas, O. Deblecquer, C. S. Ioakimidis, Applied Energy.

JA

DOI: 10.1016/j.apenergy.2017.07.035

Abstract

The evolution of smart grids enables active end-user participation in energy management systems (EMS) through demand response (DR) strategies. The integration of renewable energy sources (RES), electric vehicles (EVs) and energy storage systems (ESS) provides additional energy and storage options to a microgrid. Factors as RES generation, market prices and EVs’ driving schedule determine the benefits of microgrid’s operation. In this paper, a mixed-integer linear programming (MILP) framework-based model is provided to investigate the cooperative evaluation of an EMS operation in a building considering: (i) bidirectional energy trading capabilities of an EV fleet arriving at an office building under a stochastic EVs’ driving schedule, (ii) the impact of PV uncertainty on EMS operation based on real smart-metering data and comparing it with a deterministic PV production approach and, (iii) the effect of setting different prioritization factors in selling energy back to the grid from the resources on total system’s cost. Results confirmed the necessity of the stochastic approach as in all considered case-studies was found that the total expected daily cost for the system was much lower compared to their corresponding deterministic cases. For the base case study, detailed results were provided demonstrating the power flow between the microgrid’s components and the grid under both a stochastic and a deterministic approach.

This paper analyses the performance of the Xbee-PRO IEEE 802.15.4 (ZigBee protocol) based Wireless Area Network transmission component for urban environment, as part of the Smart City concept. This embedded solution was designed to provide a wireless networking layer for Machine-2-Machine (M2M) communication. A series of carefully designed field comparison tests in a “0” obstruction environment and a real urban area was conducted using three-dimensional positioned nodes. The objective of the study was to simulate the potential applications and expose the cases where this technology cannot be applied. The obtained results reveal significant deviation from the technical manufacturer specifications when applied in the actual field measurement environment.

2017-036: SMACCs, Preparation of a Curriculum and development of an Erasmus Mundus Joint Master degree in Smart Cities and Communities, a step towards Excellency from UMONS

Transforming cities to deal with the resource scarcity and the threats of the climate change remain major challenges in the urban development. Hence, districts are already taking an active key role in European policies. Buildings are a key consumer of energy worldwide representing over than 40% of the overall energy consumption at European level. In this current context of arising interest, reducing energy consumption is an important target. During the last years, the ‘zero energy idea’ has been introduced in international scientific literature review aiming at a more sustainable urban and built environment focusing on individual buildings by articulating the requirements for an annual basis of an energy balance equal to zero. ‘U-ZED’ (Urban-Zero Energy Districts) methodological assessment tool focuses on the challenge of zero energy objective on a district scale. In this paper, the analysis emphasises the ‘transformation’ of Bo01 Malmö area in a mixed-use zero energy district.

An impactful solution for confronting critical environmental problems may be pursued within the context of e-carpooling services. Nevertheless, a crucial part in our intervention through the introduction of efficient carpooling systems is that of the conceptualization of user preferences and attributes. This study presents a comparison between two surveys focused on a respondent sample consisting mainly of members of a university community. Specifically, the first survey involved students and employees of a private academic institution (University of Deusto, Bilbao, Spain) while the second members of a public institution in (University of Mons, Hainaut, Belgium).

This paper considers the case of São Miguel in the Azores archipelago as a typical example of an isolated island with high renewable energy potential, but largely dependent on fossil fuels incurring high import costs, in order to assess and analyse the potential impact of the plug-in hybrid electric vehicle (PHEV) technology on the local power supply system. To this end, the present work employs The Integrated MARKAL-EFOM System (TIMES) to examine a number of scenarios with different levels of PHEVs penetration under the grid-to-vehicle (G2V) approach, taking into account the established Government policies, regarding the increase in renewable energy production quotas, for the evolution of demand and supply over time. The results obtained indicate that the PHEVs integration into the local grid system under the G2V energy transferring paradigm can be realized without immediate technical barriers and bears the potential to yield significant benefits to the energy mix, reducing thus the environmental impact.

Electrification demand in small isolated power systems is typically covered by autonomous power stations, mainly diesel-generators. The technical constraints introduced by diesel-generators along with the high cost of storage options confine the penetration of renewable energy sources (RES) in these systems. This paper examines the possibility of utilizing a RES-hybrid system for a small Greek island by exploring three different case scenarios. The first two include system configurations with gradual conventional fossil-fuel power reduction while in the third one we investigate if a nearly 100% renewable system is feasible. Techno-economic analyses ensure the technical feasibility of the systems and address their economic viability. Results showed that the conventional fossil-fuel power required for the first and the second scenario could be decreased 52% and 74% compared to the existing system and the system’s overall by 17% and 26% respectively. RES-penetration reached 68% (first-scenario) and 74% (second-scenario) while the NPC value was calculated to 1.84 and 2.25 million euro respectively. A nearly 100% renewable energy system (third scenario) could be technically feasible but it would require the installation of enormous RES equipment capacity dramatically increasing the total cost. Finally, the social aspect and local acceptability of RES-projects in Greece are discussed.

Carpooling is a mobility concept that has the potential to effectively reduce the single occupancy trips with passenger cars, and thus energy consumption as well as traffic congestion, while coupled with electric vehicles (EVs) and intelligent transportation systems (ITS) can contribute to the smarter and more sustainable use of transportation networks as integrated part of smart cities. However, in practice, the success of carpooling systems has been limited by psychological barriers related to the level of trust for sharing a ride with strangers, and the necessity for convergence of schedules and trips for ride-matching. To this end, the present work advances the concept of a university-based carpooling system with EVs (e-carpooling), as a means of restricting the access to a closed community with a critical mass of users having the same origin/destination. In particular, this paper reports on the results of a preliminary survey conducted at University of Mons (UMONS), Belgium, in order to explore the characteristics of this user community with respect to the concepts of carpooling and electro-mobility. The results of the survey not only reveal the user preferences for the adoption of the proposed system, but also provide some useful insight for the implementation of the e-carpooling concept in the city of Mons.

Nowadays, one of the dominant reasons of excessive energy consumption is the high energy demand in corporate and/or public buildings. At the same time, electric vehicles (EVs) are becoming more and more popular worldwide being a considerable alternative power source when parked. In this work we initially propose an energy management framework which optimizes the control of the charging-discharging schedule of a fleet of EVs arriving at a university building for two typical load-days in February and May aiming at the minimization of the energy demand and, thus, the electricity cost of the building. To this end, a mixed integer linear programing (MILP) model containing binary and continuous variables was developed. Uncertainties in load, generation, and cost require modeling power systems with a probabilistic approach. In such a way, the probabilistic nature of demand side management (DSM) problem is also possible to be addressed. The integration of the EVs in the Low Voltage (LV) grid is simulated with a probabilistic analysis framework that uses real smart metering (SM) data. The stochastic character of the loading parameters at the network nodes is studied taking into account the charging energy needs of the corresponding EVs fleet.

Buildings are one of the main energy consumer and carbon emission sources in European countries. Population growth in cities may be effective for economic growth, but by considering overpopulated cities, making new efficient buildings and optimizing energy consumption in older ones may be a good solution for energy management and carbon reduction in them. For doing this one needs to collect buildings data for months to get an idea about the energy consumption in a building. On the other hand, computer simulations may not provide very accurate results, but they can give a crude idea about energy consumption in buildings. There are many different tools to simulate energy consumption in buildings, among all of them simplified models provide fast and accurate results. Developing building model based on lumped capacitance method by means of resistance-capacitance (RC) circuits provides good results and a comprehensive schematic about the heat transfer in the building. In this paper, the application of thermal networks for building load calculation is introduced and it will be shown how effectively it can be used in control systems to make a smart building.

Zero energy conceptual framework is attracting increasing interest in European target policies aiming at more sustainable and liveable urban and built environments. Despite its compelling context in scientific literature and practical applications, the commonly used approach is principally adopted on the aspect of an individual building. Cases with zero energy concept are few in literature. The aim of this paper is the development of a methodological approach to extend the ‘zero energy building’ to the ‘zero energy district’ by taking into account two challenges: (1) the impact of urban structure (typo-morphology) on the actual energy needs and (2) the location. It proposes a simplified methodology within three strategic axes through the systemic approach of the district and thereby opens and addresses future research perspective to be widely investigated to develop ‘smart’ districts with operational and long-term context by introducing the notion of ‘smart ground’.

High energy demand in corporate and/or public buildings is nowadays one of the main reasons of excessive energy consumption. At the same time, electric vehicles (EVs) have become very popular worldwide being a considerable alternative power source when parked. In this work we propose a scheduling mechanism which optimizes the control of the chargingdischarging schedule of an altered but finite number of EVs arriving at a university building for a typical load-day in February aiming at the minimization of the energy demand and the electricity cost of the building. In the aforementioned framework, a parallel operation of a small sized gas turbine generator (GGT) is considered. To this end, a mixed integer linear programing (MILP) model containing binary and continuous variables has been developed to optimize the control process and minimize energy cost. Results showed that the use of the EVs as an alternative energy source can significantly contribute to the reduction of the building’s energy demand leading to important cost decrease. The exploitation of the energy produced by the GGT further contributed to the minimization of the total energy consumption of the building and the total electricity cost.

Transport sector is responsible for more than 30% of European final energy consumption and carbon emissions. An increasing interest and concerns to the transportation sector has been observed to deal with the challenge of reducing the ecological footprint and the promotion of different transportation alternatives. The purpose here is twofold: first to record the everyday practices and preferences of the students at the University (Mons) regarding the use of electric bikes instead of conventional means of transport and second to explore the key factors that can influence its increasing use in the future under an electric bike sharing scheme.

This work intents to describe a new approach that would be able to combine the positive effects from the use of an E-Bike sharing system in a medium-large population urban city of Belgium demonstrated initially in case of the local University Campuses along with the use of the E-Bikes as environmental mobile sensing units.

This paper presents an overview of the electricity consumption profile and the characteristics of the power supply system in the São Miguel Island in order to assess and analyze the potential impact of the plug-in hybrid electric vehicle (PHEV) technology on the local grid. To this end, The Integrated MARKAL-EFOM System (TIMES) is employed to examine a number of sce-narios with different levels of PHEVs penetration under the grid-to-vehicle (G2V) energy transferring paradigm. In the context of our analysis, the estab-lished Government policies, regarding the increase in renewable energy produc-tion quotas, are taken into account for the evolution of demand and supply over time. The results obtained indicate that the PHEVs integration into the local grid system under the G2V model can be reA.zed without immediate technical barriers and bears the potential to yield significant benefits to the energy mix, reducing thus the environmental impact.

This paper examines the concept of utilizing plug-in electric vehicles (PEVs) and solar photovoltaic (PV) systems in large non-residential buildings for peak shaving and valley filling the power consumption profile, given that the energy cost of commercial electricity customers typically depends on both actual consumption and peak power demand within the billing period. Specifically, it describes a hybrid approach that combines an artificial neural network (ANN) for solar irradiance forecasting with a MATLAB/Simulink model to simulate the power output of solar PV systems, as well as the development of a mathematical model to control the charging/discharging process of the PEVs. The results obtained from simulating the case of the power consumption of a university building, along with experimental parking occupancy data from a university parking lot, demonstrate the applicability and effectiveness of the proposed approach.

During the last two centuries, the urban percentage of the world’s population, combined with the overall growth phenomenon, has deeply increased and it is projected to reach 60% by 2030. In this current context linked to environmental issues managing to plan sustainable cities appears a main policy target. The implementation of Zero Energy Buildings as a European target becomes a challenge for the energy savings with the significant commitment for larger urban scales. The aim of this paper is the development of a methodological systemic approach about energy management in a ‘district scale’ with zero energy context within the analysis of ten European case-studies to the potential of a ‘smart ground’ towards the development of a ‘smart city’. This work opens and addresses numerous future research perspectives that should be investigated widely to develop districts with an operational, sustainable and long-term context.

High energy demand in corporate and/or public buildings is nowadays one of the dominant reasons of excessive energy consumption. At the same time, electric vehicles (EVs) are becoming more and more popular worldwide being a considerable alternative power source when parked. In this work we propose demand response mechanism which optimizes the control of the charging-discharging schedule of an altered but finite number of EVs arriving at a university building for a typical load-day in February aiming at the minimization of the energy demand and thus the electricity cost of the building. In the aforementioned framework, a parallel operation of a small sized gas turbine is considered. To this end, a mixed integer linear programing (MILP) model containing binary and continuous variables was developed to optimize the control process and minimize energy cost.

The widespread deployment of electric vehicles (EVs), combined with the shift towards alternative modes of transportation, has the potential to alleviate the problems associated with the high use of private vehicles for commuting trips, mainly in urban areas. Authors suggest that sharing systems based on e-bikes provide a high-level service compared to conventional bike sharing systems (Fig. 1), while maintaining low environmental impacts. Yet, few studies have tried to manage their benefits in urban transportation systems and their perspectives towards the reA.zation of the ‘smart’ grid and the achievement of the visions for future cities.

This study is part of the RESIZED project. Designing new city districts and analyzing old ones from energy menagement point of view is growing idea. In RESIZED project, this goal is devided into two different parts. Urban design, energy consumption, energy production and optimization. Simplified models are a strong tool for calculating energy consumption in buildings but their application in larger scales has not been investigated yet. Until now we have developed our method to make the building’s simplified model and in second part, developing a district simplified model is under study in the RESIZED project.

The widespread deployment of electric vehicles (EVs), combined with the shift towards alternative modes of transportation, has the potential to alleviate the problems associated with the high use of private vehicles for commuting trips, mainly in urban areas. In this context, the present paper discusses a survey conducted at the University of Mons (UMONS), Belgium, in order to examine the characteristics and attitude of the students in this university community with respect to renting an electric bike (e-bike), as well as to identify the key factors that influence the use of an e-bike sharing system as integrated part of smart cities. The results of the survey indicate the preferences and intentions of the population under study to use such a system and provide some useful insight for its implementation in the city of Mons.

During the last two centuries, the urban percentage of the world’s population, combined with the overall growth phenomenon, has deeply increased and it is projected to reach 60% by 2030. In this current context linked to environmental issues managing to plan sustainable cities appears a main policy target. The European Climate and Energy package foresees a substantial reduction of energy consumptions in buildings by 2020. The implementation of Net Zero Energy Buildings (nZEBs) as the building target from 2018 onwards represents one of the biggest challenges to increase energy savings and minimize greenhouse gas emissions. The aim of this paper is the development of a methodological approach about energy management in a district to the potential of a ‘smart ground’ towards the development of a ‘smart city’. This work opens and addresses numerous future research perspectives that should be investigated widely to develop districts with an operational and long-term context.

Carsharing has the potential to reduce the total number of cars on the road, with significant benefits to the society and the environment, while at the same time relevant studies show that university communities are often more receptive to alternative transportation services compared to the general population. With the growing interest in electromobility, as a means of decarbonizing the transportation sector, this paper considers the case of combining carsharing with electric vehicles (EVs) to serve the commuting needs of students, employees and faculty of a university in Bilbao, Spain. The aim of the present work is to conceptuA.ze the design of the charging infrastructure of the e-carsharing system under a fast charging scheme and define its components, their attributes and interactions. To this end, a MATLAB/Simulink based simulator is developed incorporating the dynamics of a real-world scenario based on arrival and departure data from the university parking lot.

Nowadays distribution systems are becoming more and more complicated mainly due to the new methods of producing and storing electricity (PV, fuel cells, battery storage systems) as well as due to the new tensions of consuming electric energy (smart appliances, e-vehicles, e-bikes, etc.). Uncertainty in load, generation, and cost requires modeling power systems with a probabilistic approach. In such a way, the probabilistic nature of demand side management (DSM) problem can also be addressed. This work presents the design of an e-bike sharing system, in terms of system components and user mobility patterns. The integration of the designed system in the Low Voltage (LV) grid is simulated with a probabilistic analysis framework that uses real smart metering (SM) data. The stochastic character of the loading parameters at the network nodes is studied taking into account the charging energy needs of the proposed e-bikes sharing system. PV generation produced on the parking roof of the e-bikes smart charging stations (SCS) along with the energy stored in a local battery is also studied.

The intermittent and unstable nature of wind raises significant challenges for the operation of wind power systems, either residential installations or utility-scale implementations, necessitating the development of reliable and accurate wind power forecasting techniques. Given that wind speed forecasting is typically considered the intermediate step for wind power forecasting, the present work proposes a novel short-term wind speed forecasting model based on an artificial neural network (ANN), with the key characteristic that statistical feature parameters of wind speed, wind direction and ambient temperature are employed in order to reduce the input vector and thus the complexity of the model. The results obtained indicate that the proposed model strikes a reasonable balance between accuracy and computational requirements for a forecasting time horizon of 24 hours, providing a light-weight solution that can be integrated as part of energy management systems for small scale applications.

The present work advances the use of the Nomadic Agent (NA) concept for supporting electro-mobility through the provision of location based information in an urban environment. In the envisaged system, each NA periodically broadcasts relevant data to other mobile nodes representing electric vehicles (EVs) inside its target area. At the same time, it is considered that multiple NAs are deployed to achieve full coverage throughout an urban area, establishing a chain among different NAs over a multi-hop communication network. Moreover, the NAs exchange information with EV charging posts that play the role of the aggregators in a smart grid, i.e. intermediate actors between the power system and the users. Hence, this communication platform can support value-added functionA.ties of EVs and their integration with the power system. As a first step towards the implementation of the envisaged system, this paper focuses on modeling the NA concept with the ns-3 discrete-event network simulator in order to assess its operation under realistic conditions. The results obtained from a small-scale simulation model, yet representative of the structural components of the urban web, indicate that the proposed approach has the potential to provide a suitable solution for the communications within the active area of the NA.